Description Usage Arguments Value Note Author(s) References See Also Examples
This function extends continuity_ratio
and adds the corresponding gaussian correlation matrix for no-precipitation occurrence.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 |
data |
data frame or 'zoo' R object containing daily precipitation time series for several gauges (one gauge time series per column). See |
lag |
numeric lag (expressed as number of days) used for computation for "cross" continuity ratio and joint probability of prercipitation (no)occurrence. See |
p0_v1 |
vector for marginal probablities, see |
p |
positive integer parameter. Default is |
valmin |
threshold precipitation value [mm] for wet/dry day indicator.
If precipitation is lower than |
nearPD |
see |
interval, tolerance |
see |
only.matrix |
logical value. If |
return.value |
string. If it is not either |
null.gcorrelation |
numerical value |
sample |
character string indicated if function must be calculated differently for subset of the year, e.g. monthly. Admitted values are |
origin |
character string (yyyy-dd-mm) indicated the date of the first row of |
... |
additional agruments of |
An object which is a list containing the following fields:
continuity_ratio
: lag
-day lagged continuity ratio, as returned by continuity_ratio
;
occurrence
: joint probability of lag
-day lagged precipitation occurrence, as returned by continuity_ratio
;
nooccurrence
: joint probability of lag
-day lagged no precipitation occurrence, as returned by continuity_ratio
;
lag
: number of days lagged between the two compared events (see argument lag
);
p0_v1
: vector of marginal probability of no precipitation occurrence. If lag
is 0, it corresponds to the diagonal of nooccurrence
matrix (see argument p0_v1
);
nooccurrence_gcorrelation
corresponding gaussian correlation for no precipitation occurrence obtained by applying omega_inv
to nooccurrence
,
If the argument only.matrix
is TRUE
, only nooccurrence_gcorrelation
is returned as a matrix.
In case the argument lag
is a vector wirh length more than one, the function returns a list of the above-cited return object for each value of the vector lag
.
This functon is useful to generate the serial cross-correlation matrices for no precipitation occurrence for Yule-Walker Equations. In case lag
is a vactor, nearPD
must be a vector of the same size,
default is (lag==0)
.
See the R code for major details
Emanuele Cordano
D.S. Wilks (1998), Multisite Generalization of a Daily Stochastic Precipitation Generation Model, Journal of Hydrology, Volume 210, Issues 1-4, September 1998, Pages 178-191, https://www.sciencedirect.com/science/article/pii/S0022169498001863
Muamaraldin Mhanna and Willy Bauwens (2011) A Stochastic Space-Time Model for the Generation of Daily Rainfall in the Gaza Strip, International Journal of Climatology, Volume 32, Issue 7, pages 1098-1112, doi: 10.1002/joc.2305, https://rmets.onlinelibrary.wiley.com/doi/abs/10.1002/joc.2305
continuity_ratio
,omega_inv
,omega
,CCGammaToBlockmatrix
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 | data(trentino)
year_min <- 1961
year_max <- 1990
origin <- paste(year_min,1,1,sep="-")
period <- PRECIPITATION$year>=year_min & PRECIPITATION$year<=year_max
station <- names(PRECIPITATION)[!(names(PRECIPITATION) %in% c("day","month","year"))]
prec_mes <- PRECIPITATION[period,station]
## removing nonworking stations (e.g. time series with NA)
accepted <- array(TRUE,length(names(prec_mes)))
names(accepted) <- names(prec_mes)
for (it in names(prec_mes)) {
accepted[it] <- (length(which(!is.na(prec_mes[,it])))==length(prec_mes[,it]))
}
prec_mes <- prec_mes[,accepted]
## the dateset is reduced!!!
prec_mes <- prec_mes[,1:2]
CCGamma <- CCGamma(data=prec_mes,lag=0,tolerance=0.001,only.matrix=FALSE)
## Not Run in the examples, uncomment to run the following line
CCGamma <- CCGamma(data=prec_mes,lag=0:2,tolerance=0.001,only.matrix=FALSE)
## Not Run in the examples, uncomment to run the following line
CCGamma_monthly <- CCGamma(data=prec_mes,lag=0,tolerance=0.001,only.matrix=FALSE,
sample="monthly",origin=origin)
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